Quintevo Nigeria Limited is a consulting firm offering a range of services, including business advisory, legal, and financial services. Their offerings encompass sport advisory, financial fundraising, legal drafting of agreements, processing of specific licenses (finance, imports, exports, manufacturing, etc.), oil and gas licensing, regulatory compliance, business formation, contract drafting and review, and intellectual property management.
About the Role
We are seeking an experienced Senior Machine Learning Engineer (Level 3) to lead the design, development, and deployment of advanced machine learning models and AI-driven solutions. This role involves driving end-to-end ML lifecycle management, optimizing data pipelines, and providing technical leadership to data scientists and engineers. The successful candidate will play a key role in shaping the organization’s data science strategy and ensuring ML solutions deliver measurable business impact.
Key Responsibilities
- Lead the development, training, testing, and deployment of machine learning models.
- Oversee the design and optimization of data pipelines for ML and AI projects.
- Collaborate with data scientists, analysts, and business teams to define use cases and deliver solutions.
- Ensure scalability, performance, and reliability of ML systems in production environments.
- Evaluate new machine learning frameworks, tools, and technologies.
- Drive automation and standardization in ML workflows (MLOps).
- Provide mentorship and technical leadership to junior and mid-level ML engineers.
- Conduct reviews of ML models, algorithms, and deployment practices.
- Maintain documentation, standards, and best practices for ML engineering.
- Ensure compliance with data governance, privacy, and ethical AI practices.
Requirements
- Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, or related field.
- 5+ years’ experience as an ML Engineer or Data Scientist with production-level deployment experience.
- Strong proficiency in Python, TensorFlow, PyTorch, Scikit-learn, or similar ML frameworks.
- Experience with data pipeline tools (Airflow, Spark, Kafka) and MLOps platforms (MLflow, Kubeflow, SageMaker).
- Expertise in cloud platforms (AWS, Azure, or GCP) for ML/AI solutions.
- Strong understanding of data structures, algorithms, and statistical modeling.
- Proven ability to lead teams, mentor peers
Method of Application
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